Millions of people have spent months marching, advocating, and rallying against anti-Black violence and systemic racism. While these most recent protests were ignited by the murders of unarmed Black Americans like Breonna Taylor, George Floyd, Elijah McClain, Ahmaud Arbery, Rayshard Brooks, and others, their deaths opened many of our eyes to truths Black Americans have known for 400 years. The enslavement of people of African descent in the United States technically ended more than 150 years ago, but its legacy of racism, brutality, and discrimination persists. Black people experience racism and prejudice every day in every aspect of their lives.

Black lives matter at the Data Science Institute at Columbia University.  As we stand against anti-Black racism, we recognize that the challenge is enormous: anti-Black racism is widespread and is woven into the very fabric of this nation and will require a significant commitment to address.

We acknowledge that DSI should do more within our own unique community to address the racial equity gaps and to increase Black representation in data science research and education.  Moreover, we create training data for machine learning algorithms that often lack data relevant to the Black community and often we do not recognize that our systems unfairly discriminate against Blacks. DSI can be a critical partner and should engage in proactive measures to dismantle systemic racism, racial inequity in data science, racial inequity across the Columbia community, and racial inequity across academia more broadly. DSI strives to be a force for change. 

To that end, based on the recommendations of the DSI Task Force on Racial Equity, the initial DSI Racial Equity Action Plan includes the following:

  1. Create a faculty-led DSI Race and Equity Advisory Council by January 2021. 
  2. Add a DSI Racial Equity Statement to the DSI website.
  3. Require proposals to the DSI Seed Grant program to state explicitly how projects will ensure that the data collected and analyzed are done in a fair, just, and ethical manner.
  4. Promote research that addresses issues on racial equity and fairness in data science, e.g., in training data, machine learning algorithms and models, and automated decision making.
  5. Instill a culture of shared responsibility among DSI staff, faculty, and researchers for upholding the DSI commitment to racial equity and justice. 
  6. Actively seek racially diverse individuals to apply to DSI programs.
  7. Collaborate with university partners, including the School of Engineering and Applied Science and Arts and Sciences, on actions to support racial diversity, equity, and inclusion for the M.S. in data science program.
  8. Continue to support the DSI Task Force on Racial Equity through Fall 2020: (a) to establish partnerships with external organizations toward achieving shared goals on racial equity; (b) to address issues of climate and culture; and (c) to develop plans for a DSI Working Group on Race and Equity.  The task force will submit its final set of recommendations to Institute leadership by December 2020 and we will update this action plan accordingly.

This initial plan is just a small step toward making progress for the long term. We commit to executing this plan with the same rigor as our other research, education, and outreach efforts.